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Preoperative diagnosis of solitary pulmonary nodules with a novel hematological index model based on circulating tumor cells

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机构: [1]Department of General Internal Medicine, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China. [2]Department of Clinical Laboratory, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China. [3]Department of Radiation Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China. [4]Department of Thoracic Surgery, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China. [5]Department of Respiratory Medicine, Sichuan Academy Medical Sciences, Sichuan Provincial People's Hospital, Chengdu, China. [6]Department of Gastroenterology, Chengdu Third People's Hospital, The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China.
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关键词: pulmonary nodules diagnosis biomarkers hematological index model nomogram

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Preoperative noninvasive diagnosis of the benign or malignant solitary pulmonary nodule (SPN) is still important and difficult for clinical decisions and treatment. This study aimed to assist in the preoperative diagnosis of benign or malignant SPN using blood biomarkers.A total of 286 patients were recruited for this study. The serum FR+CTC, TK1, TP, TPS, ALB, Pre-ALB, ProGRP, CYFRA21-1, NSE, CA50, CA199, and CA242 were detected and analyzed.In the univariate analysis, age, FR+CTC, TK1, CA50, CA19.9, CA242, ProGRP, NSE, CYFRA21-1, and TPS showed the statistical significance of a correlation with malignant SPNs (P <0.05). The highest performing biomarker is FR+CTC (odd ratio [OR], 4.47; 95% CI: 2.57-7.89; P <0.001). The multivariate analysis identified that age (OR, 2.69; 95% CI: 1.34-5.59, P = 0.006), FR+CTC (OR, 6.26; 95% CI: 3.09-13.37, P <0.001), TK1 (OR, 4.82; 95% CI: 2.4-10.27, P <0.001), and NSE (OR, 2.06; 95% CI: 1.07-4.06, P = 0.033) are independent predictors. A prediction model based on age, FR+CTC, TK1, CA50, CA242, ProGRP, NSE, and TPS was developed and presented as a nomogram, with a sensitivity of 71.1% and a specificity of 81.3%, and the AUC was 0.826 (95% CI: 0.768-0.884).The novel prediction model based on FR+CTC showed much stronger performance than any single biomarker, and it can assist in predicting benign or malignant SPNs.Copyright © 2023 Zhou, He, Peng, Huang, Li, Liu, Li, Zhao, Sun, Li and He.

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大类 | 3 区 医学
小类 | 3 区 肿瘤学
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大类 | 3 区 医学
小类 | 3 区 肿瘤学
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Q2 ONCOLOGY
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Q2 ONCOLOGY

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第一作者机构: [1]Department of General Internal Medicine, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China.
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